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首页> 外文期刊>International journal of computational vision and robotics >Performance analysis on visual attention using spiking and oscillatory neural model
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Performance analysis on visual attention using spiking and oscillatory neural model

机译:基于尖峰和振荡神经模型的视觉注意性能分析

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摘要

Visual attention is a process of sustained concentration on a specific stimulus. This concentration can be increased by activating the nucleus basalis in the basal forebrain using the spiking neuron model. Input stimulus is converted into spikes. Neurons are transmitting information in the form of pulse. By using this information spiking neuron model for the basal forebrain is simulated. Bottom-up and top-down method is used in lateral geniculate nucleus (LGN). The feedback connections are applied in the visual cortex for the enhancement of visual attention. To analyse the performance of spiking and oscillatory model segmentation and separation accuracy are obtained which shows the oscillatory model produce better accuracy for visual stimuli.
机译:视觉注意力是持续专注于特定刺激的过程。通过使用尖峰神经元模型激活基底前脑中的基底核,可以增加该浓度。输入刺激转换为尖峰。神经元以脉冲形式传递信息。通过使用该信息,对基底前脑的突刺神经元模型进行了模拟。自下而上和自上而下的方法用于外侧膝状核(LGN)。反馈连接应用于视觉皮层,以增强视觉注意力。为了分析尖峰和振荡模型的性能,获得了分割和分离精度,这表明振荡模型对视觉刺激产生了更好的精度。

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